As a result of the Android system's popularity, the number of malware on it is increasing rapidly. In this study, a static detection method based on multi-feature and Stacking algorithm is proposed, which can make up the shortcomings of the two aspects, i.e., based on single feature and single algorithm. Firstly, this study uses a variety of feature information to compose the eigenvector, and uses the ensemble learning algorithm of Stacking to combine Logistic, SVM, k-Nearest Neighbor and CART decision trees. Then, classifiers are generated through training samples. The experimental results show that the recognition accuracy is up to 94.05% compared with the single feature and single algorithm, and the classifier has better recognition performance.